The seismology community is being offered an unprecedented opportunity to conduct data-driven research that will lead to fundamental changes in the way society manages the Earth and its resources. This chapter discusses requirements such as managing heterogeneous sources of data and the importance of satisfying domain experts' needs such as using existing, community-trusted analytic software. First, it introduces ambient noise processing and the key role it plays in several seismic applications. Then, it describes the implementation of the ambient noise processing on the prototype data-intensive architecture, discussing how requirements such as the integration and processing of distributed data stored on heterogeneous systems was resolved, and the importance of capturing experiment provenance data during the enactment of workflows. Finally, the chapter reflects on our experience of using the prototype data-intensive architecture and the DISPEL language.
M Galea, A Rietbrock, A Spinuso, L Trani. Data-Intensive Seismology: Research Horizons